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4D imaging, their high data rates limit their use in real-time applications. As a result, the available benchmark data for developing numerical models to predict transient multiphase flows is limited
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postharvest drying energy demand. Combining applied mycology, food safety modelling, precision agriculture and Net Zero energy systems, the research will deliver energy-efficient, data-driven grain storage
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of macrosopic quantum coherence in levitated solidstate platforms. Our Team is part of the Quantum Optics, Quantum Nanophysics and Quantum Information group of the Faculty of Physics. We are member of the Vienna
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with existing population and demographic monitoring data held by the British Trust for Ornithology. Statistical modelling approaches will examine spatiotemporal changes in bird distributions in response
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Other) The successful applicant would study an appropriate master’s degree, such as: MSc Data Science MSc in Social Data Science This project explores quantitative techniques that identify fake news
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correlation between severity ranking and human judgements. The student will work with SIE co-supervision and industry-informed glitch taxonomies and reporting requirements, under appropriate data, IP, and
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quality of this evidence to ensure it is sufficiently robust to help Welsh policy makers. For further information, please see this blog which takes stock of the Apprenticeship scheme and this article
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turbomachinery design is increasingly the primary bottleneck. Within the next decade, this workflow will be largely replaced by data-driven inverse design models, enabled by the growing availability of high
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physics-based and data-driven methods to support the design and scale-up of these systems. This approach will reduce the need for costly experiments, improve scale-up predictions, and provide confidence
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they can reliably, affordably, and fairly support a net-zero energy system. The research will focus on how data-driven and machine-learning-based control can coordinate demand, storage, and local generation